Time-Varying Modal Parameters Identification by Subspace Tracking Algorithm and Its Validation Method

Haotian Zhou,Yushu Chen,Yunhe Bai,Rui Zhao,Kaiping Yu

doi:10.1155/2018/4378793

Abstract

This article presents a time-varying modal parameter identification method based on the novel information criterion (NIC) algorithm and a post-process method for time-varying modal parameter estimation. In the practical application of the time-varying modal parameter identification algorithm, the identified results contain both real modal parameters and aberrant ones caused by the measurement noise. In order to improve the quality of the identified results as well as sifting and validating the real modal parameters, a post-process procedure based on density-based spatial clustering of applications with noise (DBSCAN) algorithm is introduced. The efficiency of the proposed approach is first verified through a numerical simulation of a cantilever Euler-Bernoulli beam with a time-varying mass. Then the proposed approach is experimentally demonstrated by composite sandwich structure in a time-varying high temperature environment. The identified results illustrate that the proposed approach can obtain real modal frequencies in low signal-to-noise ratio (SNR) scenarios.

Highlights

In the past few decades, the time-varying modal parameter identification method has attracted substantial interest in the modal analysis and testing community
The results indicate that the novel information criterion (NIC) based subspace tracking algorithm and the validation method introduced in this paper can improve the accuracy of the final results, especially for low signal-to-noise ratio (SNR) scenarios
A time-varying modal parameter identification method based on the NIC algorithm is introduced

Summary

Introduction

In the past few decades, the time-varying modal parameter identification method has attracted substantial interest in the modal analysis and testing community. The time-varying behavior is caused by the system parameters changing, such as mass properties of a flight vehicle and stiffness properties of a thermal protection system in the high temperature environment. Numerous methods have been developed under the LTV framework, such as time-frequency analysis method [1, 2]. Short time Fourier transform (STFT) has been used as an effective signal process tool in the modal analysis community, and the influence of Fourier analysis parameters has been studied in [3]. Compared to the Fourier analysis, the wavelet transform (WT) has an adjustable window size and location, and its effectiveness has been demonstrated in [4, 5]

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Conclusion